Not really. Computers have been used in economics for decades and tradeoffs between number of assumptions made and the tractability of their effects still exists if you have a machine doing the grunt work.
I mean, "rational expectations" is nothing to do with the relative simplicity of the mathematics (the models it largely replaced were worked out with pen and paper) and everything to do with the argument that economic models shouldn't rely on people making a particular type of systematic error to show a desired outcome (e.g. if policy changes required economic actors to ignore the implications of the policy change to work, they probably wouldn't actually work that well). Essentially it's the absence of an assumption about human behaviour, and there's entire classes of economic models devoted to saying "even if people on average anticipate the future and economies function perfectly smoothly, simply introducing X into the model means that you still get recessions and still get a benefit from a policy response to it", which is a more powerful argument than "if I've calibrated all these parameters and specified all these functions about all these hundreds of different types of agents' planning correctly, this policy will work", especially if you're trying to disprove arguments that the economy will sort itself out eventually.
That doesn't mean there isn't a place for complex computational models and even throwing data at ML algorithms to see what sticks, or that a general equilibrium model to predict actual changes in an economy isn't fairly unlikely yield accurate results over the long term, but they're performing an entirely different function from reasoning that X will [not] affect Y even if or only if all else is held constant or assumed to respond logically.
I disagree - by coincidence, the Blatt's book I mentioned elsewhere has a nice model of decision-making under uncertainty that is different from rational expectations. It's not more complicated.
Same goes for Keen's models, they are dynamic and pretty simple. He even writes in his books, to paraphrase, "equilibrium is feasible" was a good excuse at the beginning of 20th century, when Marshall came up with supply/demand model, but it's not today, when we can actually analyze dynamical systems mathematically.
The GP is saying that rational expectations is used not because it's simple, but because it makes the weakest assumptions about human behavior. However, I'm not sure this is entirely accurate since if some agents deviate from the equilibrium, there is no reason you couldn't end up with totally different outcomes (either better or worse).
> but because it makes the weakest assumptions about human behavior
My memory on that is little hazy (it's been maybe 15 years ago I read about it), but as I remember this was the case about Blatt's model as well. And IIRC it's based on earlier ideas by Keynes (uncertainty is a different thing than risk).
I also recall nice idea from Paul Ormerod (but it could have been somebody else or folklore) who had an interesting model of economic agents - do either one of the 3 things:
- the thing that you always did
- the thing that others are doing
- another thing that you think might work
This also leads to an interesting class of models (different from rational expectations) and it's not making too much assumptions about humans.
Again, this shows that Blatt and Keen (and other post-keynesians) are woefully underappreciated in economics.
I'm unfamiliar with Blatt's book (sounds interesting) but assumptions about humans attempting to predict the future don't really get any simpler than human misjudgements of the future don't follow a pattern an economist can predict (and to a lesser extent, companies try to make more profit where possible is also a pretty weak assumption). Especially when the whole reason this came to be popular was the analytical tearing apart of theories which used reasonable sounding alternatives people will base their expectations on what happened last time by pointing out that some people - even a minority - would make enormous amounts of money if chose to behave differently from how the economist said people would would behave, or that "I would like my wages to be the same as last year" would be a really stupid thing for workers to bargain for if the government has stated they're trying to boost the economy by purposely creating inflation. The other side of that argument is there are some conclusions drawn from some rational expectations models which are a bit too dependent on the assumption that people [on average] won't make prediction errors at all.
I've got plenty of time for the post-Keynesians but most of them (particularly in the Keen Godley/Lavoie Social Accounting Matrix style) really aren't doing more complicated mathematics so much as choosing to have models far more sensitive to specified lag structures and/or using different assumptions about human behaviour (The flip side is that Keen's hypersensitive-to-how-it's-specified banking system is better in many respects than a macro model with no banking system or credit constraints)
For much of the last century the Cambridge post Keynesians distinguished themselves by doing a lot less modelling than their neoclassical counterparts.
We have the models, but economists have been surprisingly resistant to mainstream mathematical tools and often treat fields as scalars. A single consumer price index makes about as much sense as a single temperature measurement for an entire country.
IIRC prominent economists actively ridiculed the idea of a "Manhattan Project" a few years back. The idea was to pull in experts from mathematics, physics, biology and computer science to invigorate the field via cross-pollination like occurred with mathematics and physics in the 70s and economists did not like it.
Update: apparently it did lead to a conference, at least, and Nassim Taleb was one of the participants.
I mean, "rational expectations" is nothing to do with the relative simplicity of the mathematics (the models it largely replaced were worked out with pen and paper) and everything to do with the argument that economic models shouldn't rely on people making a particular type of systematic error to show a desired outcome (e.g. if policy changes required economic actors to ignore the implications of the policy change to work, they probably wouldn't actually work that well). Essentially it's the absence of an assumption about human behaviour, and there's entire classes of economic models devoted to saying "even if people on average anticipate the future and economies function perfectly smoothly, simply introducing X into the model means that you still get recessions and still get a benefit from a policy response to it", which is a more powerful argument than "if I've calibrated all these parameters and specified all these functions about all these hundreds of different types of agents' planning correctly, this policy will work", especially if you're trying to disprove arguments that the economy will sort itself out eventually.
That doesn't mean there isn't a place for complex computational models and even throwing data at ML algorithms to see what sticks, or that a general equilibrium model to predict actual changes in an economy isn't fairly unlikely yield accurate results over the long term, but they're performing an entirely different function from reasoning that X will [not] affect Y even if or only if all else is held constant or assumed to respond logically.